Research on Music Intelligent Recommendation System Based on Spark Framework and Hybrid Algorithm

Abstract

In view of the intelligent demand of music education model, this paper proposes to apply the hybrid recommendation algorithm in music intelligent recommendation to improve the accuracy of music recommendation. Among them, the advantages of collaborative filtering algorithm and tag recommendation algorithm are combined. The results show that when the time weight factor is 0.7, the accuracy, recall and F1 index value of the hybrid recommendation algorithm are stable. Compared with the algorithm before improvement and the label clustering recommendation algorithm, the hybrid recommendation algorithm has the best effect and superiority. At the same time, when the algorithm is applied to the system recommendation, it also obtains good recommendation effect. Therefore, the constructed hybrid recommendation algorithm and system based on big data and artificial intelligence can meet the needs of intelligent upgrading of music education mode.